Loading required package: ursa
knit <- ursa:::.isKnitr()
simplify <- 4
g1 <- regrid(bbox=c(0,-90,360,90),crs=NA,res=simplify*2.5/60)
ursa_crs(g1) <- 4326
g1List of 9
$ columns: int 2160
$ rows : int 1080
$ resx : num 0.167
$ resy : num 0.167
$ minx : num 0
$ maxx : num 360
$ miny : num -90
$ maxy : num 90
$ crs : chr "+init=epsg:4326"
- attr(*, "class")= chr ".ursaGrid"
Размер растра:
lines samples
1080 2160
Число точек в контурах/полигонов водоемов:
[1] 8000
lon <- runif(n,min=0,max=360)
lat <- runif(n,min=-85,max=85)
hydro <- ursa:::spatialize(data.frame(lon=lon,lat=lat,value=2L),crs=4326)
session_grid(g1)
spatial_coordinates(hydro) |> summary() x y
Min. : 0.0262 Min. :-84.9843
1st Qu.: 90.9261 1st Qu.:-41.7339
Median :182.1642 Median : 1.1218
Mean :180.6053 Mean : 0.8342
3rd Qu.:271.9678 3rd Qu.: 43.4293
Max. :359.8630 Max. : 84.9810
*** render.R: distance -- start: 5.30(5.00) seconds ***
res <- ursa:::.dist2(world,hydro,summarize=FALSE
,spherical=TRUE
,verbose=!ursa:::.isKnitr())["dist"]
ursa:::.elapsedTime("distance -- finish")*** render.R: distance -- finish: 1037.15(1031.85) seconds ***
name mean sd sum min max n nNA
[2] dist 344.4 115.791 803415905 8.39754 745.864 2332800 0